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Microwave neural modeling for silicon FinFET varactors
Author(s) -
Marinković Zlatica,
Crupi Giovanni,
Schreurs Dominique M. M.P.,
Caddemi Alina,
Marković Vera
Publication year - 2014
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.1926
Subject(s) - varicap , microwave , cmos , transistor , electronic engineering , artificial neural network , embedding , electrical engineering , computer science , materials science , engineering , capacitance , physics , telecommunications , artificial intelligence , voltage , electrode , quantum mechanics
SUMMARY The FinFET architecture is currently attracting increasing attention to enable further downscaling of the complementary metal–oxide–semiconductor (CMOS) technology. The interest towards the FinFET technology for microwave applications is not only limited to transistors but extended also to varactors. Therefore, there is a need for efficient and accurate varactor models in the high‐frequency range. In this paper, an artificial neural network‐based behavioral model of varactors fabricated in advanced FinFET technology is proposed. The model is developed and verified by comparing measured and simulated scattering parameters up to 50 GHz. The extracted model can reproduce very well the measured behavior of the tested varactor before and after applying the de‐embedding procedure based on open dummy structure. Copyright © 2014 John Wiley & Sons, Ltd.